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Visual Recognition Course (March April 2019)

Basic Info

  • Where: IIIT-Bangalore
  • When: March/April 2019
  • Who: Anush Sankaran, IBM Research AI (co-instructed with Prof. Dinesh Babu Jayagopi)

Course Overview

Date Topic Content Slides Notes
22nd March, 2019 (Friday) Introduction to Image Classification, Neural Networks, and Optimization - What is visual recognition? - Logistic regression - Stochastic Gradient Descent - Multilayer perceptron - Backpropagation - DL + ML Pipeleine slides
30th March, 2019 (Saturday) Unsupervised Feature Learning, Autoencoders, Convolutional Neural Networks - Popular applications of DL - Stacked autoencoders - Convolution & Pooling layers - Convolutional autoencoder slides Notebook
6th April, 2019 (Saturday) Hyper-parameter optimization, Training Process Convolutional neural network - One time model setup - Hyper-parameter optimization slides Notebook
10th April, 2019 (Wednesday) Different CNN Architectures Data Augmentation - Transfer Learning - Comparison of Different CNN Architectures - Watson Studio Hands-on slides Watson Studio: How To
20th April, 2019 (Saturday) Generative Modelling Unsupervised learning - Distribution fitting - PixelRNN/CNN - Variational Autoencoder (VAE) - Generative Adversarial Network (GAN) - Open source GAN toolkit slides Open source GAN Toolkit
27th April, 2019 (Saturday) CNN Visualization and Face Recognition Neuron Visualization - Guided BackProp - Grad-CAM - Face Classification - Face Generation - DeepFake - Model Trust slides

Acknowledgement

References and they have better slides! With huge respects to their slides, hard work, and efforts, I acknowledge them and only makes sense to reuse some part of their slides!

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Course notes, some coding, assignments, and etc.

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